Evidence map›Paper›PMID 38001356›Full record

ReviewNature reviews. Clinical oncology2024

Personalizing adjuvant therapy for patients with colorectal cancer.

Li Yang, Jinlin Yang, Andreas Kleppe, Håvard E Danielsen, David J Kerr

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Clinical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

74 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  6. Universal off-the-shelf TGF-Acta pharmaceutica Sinica. B · 2026
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14 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Li Yang *Department of Gastroenterology, Sichuan University, Chengdu, China.
Jinlin Yang *Department of Gastroenterology, Sichuan University, Chengdu, China.
Andreas KleppeInstitute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway.ORCID http://orcid.org/0000-0002-8370-5289
Håvard E DanielsenInstitute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway.ORCID http://orcid.org/0000-0002-6798-4724
David J KerrRadcliffe Department of Medicine, Oxford University, Oxford, UK. david.kerr@ndcls.ox.ac.uk.ORCID http://orcid.org/0000-0001-7811-6722

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current standard-of-care adjuvant treatment for patients with colorectal cancer (CRC) comprises a fluoropyrimidine (5-fluorouracil or capecitabine) as a single agent or in combination with oxaliplatin, for either 3 or 6 months. Selection of therapy depends on conventional histopathological staging procedures, which constitute a blunt tool for patient stratification. Given the relatively marginal survival benefits that patients can derive from adjuvant treatment, improving the safety of chemotherapy regimens and identifying patients most likely to benefit from them is an area of unmet need. Patient stratification should enable distinguishing those at low risk of recurrence and a high chance of cure by surgery from those at higher risk of recurrence who would derive greater absolute benefits from chemotherapy. To this end, genetic analyses have led to the discovery of germline determinants of toxicity from fluoropyrimidines, the identification of patients at high risk of life-threatening toxicity, and enabling dose modulation to improve safety. Thus far, results from analyses of resected tissue to identify mutational or transcriptomic signatures with value as prognostic biomarkers have been rather disappointing. In the past few years, the application of artificial intelligence-driven models to digital images of resected tissue has identified potentially useful algorithms that stratify patients into distinct prognostic groups. Similarly, liquid biopsy approaches involving measurements of circulating tumour DNA after surgery are additionally useful tools to identify patients at high and low risk of tumour recurrence. In this Perspective, we provide an overview of the current landscape of adjuvant therapy for patients with CRC and discuss how new technologies will enable better personalization of therapy in this setting.

Indexed as

Colorectal NeoplasmsAntineoplastic Combined Chemotherapy ProtocolsArtificial IntelligenceCapecitabineChemotherapy, AdjuvantFluorouracilHumansNeoplasm Recurrence, LocalCapecitabineFluorouracil

Identifiers

PMID38001356

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.